Faculty of Business and Management Sciences · Economics · Undergraduate
ECTS: 5 T+P+L: 3+0+0 Compulsory
Coordinator:
Course Objective
This course focuses on statistical methods used in data analysis and decision-making. Topics include confidence intervals, hypothesis testing, comparisons of means and proportions, correlation and regression, chi-square tests, analysis of variance (ANOVA), nonparametric statistics, and sampling techniques. Emphasis is placed on practical applications in business, economics, and engineering.
Course Content
Expectations and Goals:
By the end of this course, students should be able to:
- Construct and interpret confidence intervals.
- Perform hypothesis testing and analyze differences between groups.
- Apply correlation and regression techniques to real-world data.
- Use chi-square tests and ANOVA for categorical and variance analysis.
- Implement nonparametric statistical methods when appropriate.
- Understand sampling techniques and their role in statistical inference.
Students are expected to actively participate, apply statistical tools using software, and develop analytical problem-solving skills.
Course Learning Outcomes
- Understands and applies nonparametric statistical methods for data analysis.
- Communicates statistical findings through tables, graphs, and technical reports.
- Recognizes and explains the principles of linear regression and correlation analysis.
- Understands and applies the concepts of multiple linear regression and certain nonlinear regression models.
- Analyzes data using one-factor experimental designs and general ANOVA techniques.
- Designs and evaluates factorial experiments involving two or more factors.
- Implements 2^𝑘 factorial experiments and fractional factorial designs for process optimization.
- Uses R or similar software for statistical analyses.
Core Area Distribution
(46) Mathematics and Statistics%60 (52) Engineering and Engineering Trades%40